Videomae Base Finetuned Kinetics 0407 Final 5sec Bbox Retry

--- library_name: transformers license: cc-by-nc-4.0 base_model: MCG-NJU/videomae-base-finetuned-kinetics tags: - generated_from_trainer metrics: - accuracy model-index: - name: videomae-base-finetuned-kinetics-0407_final_5sec_bbox_retry results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # videomae-base-finetuned-kinetics-0407_final_5sec_bbox_retry This model is a fine-tuned version of [MCG-NJU/videomae-base-finetuned-kinetics](https://huggingface.co/MCG-NJU/videomae-base-finetuned-kinetics) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.5853 - Accuracy: 0.8268 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.05 - training_steps: 64400 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-------:|:----:|:---------------:|:--------:| | 0.0064 | 0.0087 | 560 | 0.2854 | 0.9155 | | 0.027 | 1.0087 | 1120 | 0.4700 | 0.8591 | | 0.0034 | 2.0087 | 1680 | 0.8010 | 0.8127 | | 0.1029 | 3.0087 | 2240 | 0.7237 | 0.8145 | | 0.0282 | 4.0087 | 2800 | 1.3460 | 0.6745 | | 0.028 | 5.0087 | 3360 | 0.4030 | 0.8855 | | 0.0029 | 6.0087 | 3920 | 0.5687 | 0.8655 | | 0.0034 | 7.0087 | 4480 | 0.6655 | 0.8291 | | 0.101 | 8.0087 | 5040 | 0.7841 | 0.8264 | | 0.3789 | 9.0087 | 5600 | 2.0764 | 0.6673 | | 0.0908 | 10.0087 | 6160 | 1.0014 | 0.7827 | | 0.0005 | 11.0087 | 6720 | 0.6949 | 0.8545 | | 0.2388 | 12.0087 | 7280 | 1.9325 | 0.6973 | | 0.0004 | 13.0087 | 7840 | 1.0476 | 0.7864 | | 2.0909 | 14.0087 | 8400 | 0.9193 | 0.8227 | | 0.0047 | 15.0087 | 8960 | 2.3364 | 0.6755 | ### Framework versions - Transformers 4.48.0 - Pytorch 2.5.1+cu124 - Datasets 3.2.0 - Tokenizers 0.21.0